With the development of information technique and the coming of the network era, it is more and more popular to search information to obtain the needed data by using the network.
Searching information includes the following steps. Firstly, a user terminal sends a search request including a query word to a server for searching. After receiving the search request, the server makes a search and obtains search resulting items, and then initially ranks all the search resulting items and feedback the ranked resulting item to the user terminal.
In general, a user click log is often used to initially rank the respective search resulting items. The user click log records the information on the respective query words inputted by the user, which includes the item clicks ratio of the respective search resulting item associated with the query word. The item clicks ratio of a search resulting item associated with the query word is a value obtained by dividing the total click times that the user clicks the search resulting item associated with the query word by the times that the user searches the query word.
At present, item clicks ratios are often used to rank search resulting items. Specifically, search resulting items are ranked in descending order of item clicks ratios. The item clicks ratio indicates directly the satisfaction degree of search result. In general, the more the clicks ratio of a search resulting item is, the higher the user satisfaction degree of the search results item is and thus the more highly the search result item should be ranked. However, the item clicks ratio itself is also affected by search result ranking. The topper a search resulting item is ranked, the greater the probability that the item is clicked is. Therefore, it not sure that the search result item is ranked highly based on the item clicks ratio is the item whose requirement degree of the user is high. Such case is called a sequence inaccuracy problem. The sequence inaccuracy problem demonstrates that ranking the search resulting items only based on item clicks ratios is not accurate and such ranking method is unfair for a search result item which is ranked lower.
In order to solve the sequence inaccuracy problem, a manual adjusting ranking method is often used to rank search resulting items. In this method, position compensation factors are set for the respective ranking positions. The ranking positions refer to the sequences of the search resulting items, such as the first position, the second position, the third position, the forth position, the fifth position . . . and so on. Each ranking position has a corresponding compensation factor is an empirical value obtained through manual adjusting and a set of adjusted compensation factors are suitable to all search result ranking.
The existing manual adjusting ranking method includes the following steps. Firstly, a user terminal sends a search request including a query word to a server for searching. After receiving the search request, the server makes a search and obtains search resulting items, reads the item clicks ratio of the respective search resulting items from the user click log, assigns a compensation factor to each ranking position, multiplies the item clicks ratio of the respective search resulting items by the corresponding compensation factor so as to obtain ranking scores of the search resulting items, and then ranks all the search resulting items in descending order of the ranking scores and feedbacks the ranked resulting item to the user terminal.
In the existing manual adjusting rank solutions, the compensation factor of each ranking position is an empirical value obtained through manual adjusting, and a set of adjusted compensation factors are applied to all search result rankings. Such method using an empirical value to determine the compensation factor is too coarse, and letting a set of compensation factors suit to all search result ranking will cause the compensation inaccurate, and therefore cause the ranking result can not satisfy the query requirement of the user.